Diffuse Optical Imaging Is an Emerging Modality That Usesnear Infrared (Nir) Light to Reveal Structural and Functional Information Ofdeep Biological Tissue. It Provides Contrast Mechanisms For Molecular,Chemical, and Anatomical Imaging That Is Not Available from Other Imagingmodalities. Diffuse Optical Tomography (Dot) Deals With 3D Reconstruction Ofoptical Properties of Tissue Given the Measurements and a Forward Model Ofphoton Propagation. Dot Has Inherently Low Spatial Resolution Due to Diffusenature of Photons. In This Work, We Focus to Improve the Spatial Resolution Andthe Quantitative Accuracy of Dot By Using a Priori Anatomical Informationspecific to Unknown Image. Such Specific a Priori Information Can Be Obtainedfrom a Secondary High-Resolution Imaging Modality Such As Magnetic Resonance(Mr) or X-Ray. Image Reconstruction Is Formulated Within a Bayesian Frameworkto Determine the Spatial Distribution of the Absorption Coefficients of Themedium. a Spatially Varying a Priori Probability Density Function Is Designedbased on the Segmented Anatomical Information. Conjugate Gradient Method Isutilized to Solve the Resulting Optimization Problem. Proposed Method Isevaluated Using Simulation and Phantom Measurements Collected With a Noveltime- Resolved Optical Imaging System. Results Demonstrate That the Proposedmethod Leads to Improved Spatial Resolution, Quantitative Accuracy and Fasterconvergence Than Standard Least Squares Approach. Diffuse Optical Tomography (Dot) Ls a Se ...